Skip to main navigation menu Skip to main content Skip to site footer

Vol. 17 No. 1 (2023)

Vegetable section

Variability, correlation, and path analysis in erect and prostrate cultivars of cowpea (Vigna unguiculata [L.] Walp.)

https://doi.org/10.17584/rcch.2023v17i1.15508

Published 2023-01-01

  • Hérmes Araméndiz-Tatis
    • ,
  • Miguel Espitia-Camacho
    • ,
  • Carlos Cardona-Ayala

Hérmes Araméndiz-Tatis
Universidad de Córdoba, Monteria

Miguel Espitia-Camacho
Universidad de Córdoba, Monteria

Carlos Cardona-Ayala
Universidad de Córdoba, Monteria

Evaluation of cowpea cultivars. Photo: L.A. Perneth

Abstract

The cowpea bean (Vigna unguiculata [L.] Walp.) is the most important legume in the Colombian Caribbean, and is cultivated with genotypes having prostrate growth habit, with yields that do not exceed 700 kg ha-1. Manual harvesting is very expensive for crop rotation in commercial agriculture, which is why cultivars with erect growth habit are required. The research was carried out in the first semester of 2022, in the experimental area of the Universidad de Córdoba (Monteria-Colombia). Sixteen erect genotypes and five prostrate genotypes, including the control, were evaluated under a randomized complete block design with five repetitions. Each experimental unit consisted of two rows of 5 m in length, with a distance between plants of 0.15 m and between rows of 0.40 m for a population density of 166.000 plants/ha. The results indicated genetic variability, which enables successful phenotypic selection, according to the estimated genetic parameters. Likewise, there was positive and significant correlations of performance components with yield. In addition, the unfolding of genotypic correlations by means of path analysis indicated that grain thickness is an important and easy to measure characteristic to increase yield.

Keywords

Legumes, Grain quality, Genetic variability, Food security, Nutritional composition

PDF

References

  1. Abaidoo, R., M.O. Dare, S. Killani, and A. Opoku. 2017. Evaluation of early maturing cowpea (Vigna unguiculata) germplasm for variation in phosphorus use efficiency and biological nitrogen fixation potential with indigenous rhizobial populations. J. Agric. Sci. 155(1), 102-116. Doi: https://doi.org/10.1017/S002185961500115X
  2. Agronet. 2022. Área, producción y rendimiento nacional por cultivo. In: https://www.agronet.gov.co/estadistica/paginas/home.aspx?cod=1; consulted: October, 2022.
  3. Bandi, H.R.K., K.N. Rao, K.V. Krishna, and K. Srinivasulu. 2018. Correlation and path-coefficient estimates of yield and yield component traits in rice fallow blackgram (Vigna mungo (L.) Hepper). Int. J. Curr. Microbiol. App. Sci. 7(3), 3304-3309. Doi: https://doi.org/10.20546/ijcmas.2018.703.380
  4. Cardona-Ayala, C., H. Araméndiz-Tatis, and A. Jarma-Orozco. 2013. Variabilidad genética en líneas de fríjol caupí (Vigna unguiculata L. Walp). Rev. Agron. 21(2), 7-18.
  5. Carvalho, A.F.U., N.M. Sousa, D.F. Farias, L.C.B. Rocha-Bezerra, R.M.P. Silva, M.P. Viana, S.T. Gouveia, S.S. Sampaio, M.B. Sousa, G.P.G. Lima, S.M. Morais, C.C. Barros, and F.R. Freire Filho. 2012. Nutritional ranking of 30 Brazilian genotypes of cowpeas including determination of antioxidant capacity and vitamins. J. Food Compos. Anal. 26(1-2), 81-88. Doi: https://doi.org/10.1016/j.jfca.2012.01.005
  6. Cruz, C.D. 2016. Programa Genes V.2016.6.0 - Aplicativo computacional em genética e estatística. In: http://www.ufv.br/dbg/genes/genes.htm; consulted: October, 2022.
  7. Dinesh, H.B., K.P. Viswanatha, H.C. Lohithaswa, R. Pavan, and P. Singh. 2017. Variability, correlation and path analysis studies in F3 generation of cowpea [Vigna unguiculata (L.) Walp]. Int. J. Curr. Microbiol. Appl. Sci. 6(9), 1420-1428. Doi: https://doi.org/10.20546/ijcmas.2017.609.172
  8. Donkor, E.F., R.R. Adjei, B. Amadu, and A.S. Boateng. 2022. Genetic variability, heritability and association among yield components and proximate composition of neglected and underutilized Bambara groundnut [Vigna subterranea (L.) Verdc] accessions for varietal development in Ghana. Heliyon 8(6), e09691. Doi: https://doi.org/10.1016/j.heliyon.2022.e09691
  9. Espinosa, V. 2018. Construcción y análisis de los coeficientes de sendero. Acta Nova 8(4), 517-535.
  10. Johnson, H.W., H.F. Robinson, and R.E. Comstock. 1955. Estimates of genetic and environmental variability in soybeans. Agron. J. 47(7), 314-318. Doi: https://doi.org/10.2134/agronj1955.00021962004700070009x
  11. Jost, E., N.D. Ribeiro, S.M. Maziero, M.T.D.F. Possobom, D.P. Rosa, and L.S. Domingues. 2013. Comparison among direct, indirect and index selections on agronomic traits and nutritional quality traits in common bean. J. Sci. Food Agric. 93(5), 1097-104. Doi: https://doi.org/10.1002/jsfa.5856
  12. Lekshmanan, D.K. and M.A. Vahab. 2017. Correlation and path coefficient analysis of yield and its component characters among different accessions of cluster bean [Cyamopsis tetragonoloba (L.) Taub.]. Legume Res. 41(1), 53-56. Doi: https://doi.org/10.18805/10.18805/LR-3691
  13. Mafakheri, K., M.R. Bihamta, and A.R. Abbasi. 2017. Assessment of genetic diversity in cowpea (Vigna unguiculata L.) germplasm using morphological and molecular characterization. Cogent Food Agric. 3(1), 1327092. Doi: https://doi.org/10.1080/23311932.2017.1327092
  14. Martínez-Reina, A.M., C.C. Cordero-Cordero, and A.P. Tofiño-Rivera. 2022. Eficiencia técnica del frijol caupí (Vigna unguiculata L. Walp) en la Región Caribe de Colombia. Agron. Mesoam. 33(2), 47673. Doi: https://doi.org/10.15517/am.v33i2.47673
  15. Osipitan, O.A., J.S. Fields, S. Lo, and I. Cuvaca. 2021. Production systems and prospects of cowpea (Vigna unguiculata (L.) Walp.) in the United States. Agronomy 11(11), 2312. Doi: https://doi.org/10.3390/agronomy11112312
  16. Paltridge, N.G., L.J. Palmer, P.J. Milham, G.E. Guild, and J.C.R. Stangoulis. 2012. Energy-dispersive X-ray fluorescence analysis of zinc and iron concentration in rice and pearl millet grain. Plant Soil 361(1-2), 251-260. Doi: https://doi.org/10.1007/s11104-011-1104-4
  17. Panchta, R., Preeti, and S. Arya. 2020. Variability, correlation and path analysis studies in grain cowpea [Vigna unguiculata (L.) Walp]. Indian J. Pure Appl. Biosci. 8(2), 169-172. Doi: http://doi.org/10.18782/2582-2845.8035
  18. Prasad, S.R., R. Prakash, C.M. Sharma, and M.F. Haque. 1981. Genotypic and phenotypic variability in quantitative characters in oat. Indian J. Agric. Sci. 51(7), 480-482.
  19. Silva, A.C., O.M. Morais, J.L. Santos, L.O. d’Arede, C.J. Silva, and M.M. Rocha. 2014. Estimativa de parâmetros genéticos em Vigna unguiculata. Rev. Cienc. Agrar. 37(4), 399-407.
  20. Singh, B.B. 2007. Recent progress in cowpea genetics and breeding. Acta Hortic. 752, 69-76. Doi: http://doi.org/10.17660/ActaHortic.2007.752.7
  21. Singh, P., S. Prasad, and W. Aalbersberg. 2016. Bioavailability of Fe and Zn in selected legumes, cereals, meat, and milk products consumed in Fiji. Food Chem. 207(15), 125-131. Doi: http://doi.org/10.1016/j.foodchem.2016.03.029
  22. Singh, A., Shweta, and V. Singh. 2018. Estimates of genetic variability, heritability and genetic advance for yield and yield component traits in Indian cowpea [Vigna unguiculata (L.) Walp.]. Int. J. Pure App. Biosci. 6(1), 1142-1147. Doi: http://doi.org/10.18782/2320-7051.5978
  23. Tirkey, M., G.M. Lal, and S.P. Anand. 2022. Estimation of correlation and path analysis for quantitative traits in cowpea (Vigna unguiculata (L.) Walp). Int. J. Plant Soil Sci. 34(22), 1194-1200. Doi: https://doi.org/10.9734/ijpss/2022/v34i2231486
  24. Varanya, A., G. Gayathri, K. Arya, C.T. Usha, P.G. Pratheesh, and H. Priyanka. 2022. Genetic variability and genetic parameters analysis of 143 fodder cowpea [Vigna unguiculata (L.) Walp] germplasm accessions for yield and yield attributing traits. Pharma Innov. J. 11(2), 2595-2600.
  25. Xiong, H., A. Shi, B. Mou, J. Qin, D. Motes, W. Lu, J. Ma, Y. Weng, W. Yang, and D. Wu. 2016. Genetic diversity and population structure of cowpea (Vigna unguiculata L. Walp). PLoS One 11(8), e0160941. Doi: http://doi.org/10.1371/journal.pone.0160941

Downloads

Download data is not yet available.

Most read articles by the same author(s)

Similar Articles

1 2 3 4 > >> 

You may also start an advanced similarity search for this article.